Examples of org.apache.commons.math.stat.descriptive.moment.Kurtosis

Package org.apache.commons.math.stat.descriptive.moment

Examples of org.apache.commons.math.stat.descriptive.moment.Kurtosis

org.apache.commons.math.stat.descriptive.moment.Kurtosis
Computes the Kurtosis of the available values.
We use the following (unbiased) formula to define kurtosis:

kurtosis = { [n(n+1) / (n -1)(n - 2)(n-3)] sum[(x_i - mean)^4] / std^4 } - [3(n-1)^2 / (n-2)(n-3)]
where n is the number of values, mean is the {@link Mean} and std is the{@link StandardDeviation}

Note that this statistic is undefined for n < 4. Double.Nan is returned when there is not sufficient data to compute the statistic.

Note that this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes the increment() or clear() method, it must be synchronized externally.
@version $Revision: 1006299 $ $Date: 2010-10-10 16:47:17 +0200 (dim. 10 oct. 2010) $


        FourthMoment m4 = new FourthMoment();
        Mean m = new Mean(m4);
        Variance v = new Variance(m4);
        Skewness s= new Skewness(m4);
        Kurtosis k = new Kurtosis(m4);


        for (int i = 0; i < testArray.length; i++){
            m4.increment(testArray[i]);
        }


        assertEquals(mean,m.getResult(),tolerance);
        assertEquals(var,v.getResult(),tolerance);
        assertEquals(skew ,s.getResult(),tolerance);
        assertEquals(kurt,k.getResult(),tolerance);


    }

View Full Code Here

        
        FourthMoment m4 = new FourthMoment();
        Mean m = new Mean(m4);
        Variance v = new Variance(m4);
        Skewness s= new Skewness(m4);
        Kurtosis k = new Kurtosis(m4);


        for (int i = 0; i < testArray.length; i++){
            m4.increment(testArray[i]);
        }
        
        assertEquals(mean,m.getResult(),tolerance);
        assertEquals(var,v.getResult(),tolerance);
        assertEquals(skew ,s.getResult(),tolerance);
        assertEquals(kurt,k.getResult(),tolerance);


    }

View Full Code Here

     * measure of the "peakedness" of a distribution
     * @return The kurtosis, Double.NaN if no values have been added, or 0.0 
     * for a value set &lt;=3. 
     */
    public double getKurtosis() {
        return apply(new Kurtosis());
    }

View Full Code Here


        FourthMoment m4 = new FourthMoment();
        Mean m = new Mean(m4);
        Variance v = new Variance(m4);
        Skewness s= new Skewness(m4);
        Kurtosis k = new Kurtosis(m4);


        for (int i = 0; i < testArray.length; i++){
            m4.increment(testArray[i]);
        }


        assertEquals(mean,m.getResult(),tolerance);
        assertEquals(var,v.getResult(),tolerance);
        assertEquals(skew ,s.getResult(),tolerance);
        assertEquals(kurt,k.getResult(),tolerance);


    }

View Full Code Here

        
        FourthMoment m4 = new FourthMoment();
        Mean m = new Mean(m4);
        Variance v = new Variance(m4);
        Skewness s= new Skewness(m4);
        Kurtosis k = new Kurtosis(m4);


        for (int i = 0; i < testArray.length; i++){
            m4.increment(testArray[i]);
        }
        
        assertEquals(mean,m.getResult(),tolerance);
        assertEquals(var,v.getResult(),tolerance);
        assertEquals(skew ,s.getResult(),tolerance);
        assertEquals(kurt,k.getResult(),tolerance);


    }

View Full Code Here

     * measure of the "peakedness" of a distribution
     * @return The kurtosis, Double.NaN if no values have been added, or 0.0 
     * for a value set &lt;=3. 
     */
    public double getKurtosis() {
        return apply(new Kurtosis());
    }

View Full Code Here

        
        FourthMoment m4 = new FourthMoment();
        Mean m = new Mean(m4);
        Variance v = new Variance(m4);
        Skewness s= new Skewness(m4);
        Kurtosis k = new Kurtosis(m4);


        for (int i = 0; i < testArray.length; i++){
            m4.increment(testArray[i]);
        }
        
        assertEquals(mean,m.getResult(),tolerance);
        assertEquals(var,v.getResult(),tolerance);
        assertEquals(skew ,s.getResult(),tolerance);
        assertEquals(kurt,k.getResult(),tolerance);


    }

View Full Code Here

        
        FourthMoment m4 = new FourthMoment();
        Mean m = new Mean(m4);
        Variance v = new Variance(m4);
        Skewness s= new Skewness(m4);
        Kurtosis k = new Kurtosis(m4);


        for (int i = 0; i < testArray.length; i++){
            m4.increment(testArray[i]);
        }
        
        assertEquals(mean,m.getResult(),tolerance);
        assertEquals(var,v.getResult(),tolerance);
        assertEquals(skew ,s.getResult(),tolerance);
        assertEquals(kurt,k.getResult(),tolerance);


    }

View Full Code Here

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org.apache.commons.math.stat.descriptive.DescriptiveStatistics

org.apache.commons.math.stat.descriptive.InteractionTest

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